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An Organic, Conducive, Habitable MultiUniVerse

Ensslin, Torsten, et al. The Physics of Information. Annalen der Physik. 531/3, 2019. An MPI Astrophysics theorist introduces a special Physics of Information issue in this European journal in print since 1799. Some 320 years later this distinctive quality, not evident until our 21st century, has become a primary feature of what can be known as physical reality. In regard, the lead paper is Information and the Reconstruction of Quantum Physics by Gregg Jaeger (herein), see also Information Theory for Fields by T. Ensslin, and Entropic Dynamics: Quantum Mechanics from Entropy and Information Geometry by Ariel Caticha.

Information is virtual. It can be carried by speech, an image, scratches on a stone, patterns in a photon field, the connections of neurons in our brains or even by the wavefunction of an electron. Information does not depend on the actual means of transmission. Information is physical. It needs to be sustained by a physical substrate which requires energy or work. Without a physical world, information can not be stored, processed, or transmitted. Actually information about the physical laws governing our Universe can be found everywhere and in everything. Could it then be that the real fundamental elements of this world are tiny bits of information? (1)

Jaeger, Gregg. Information and the Reconstruction of Quantum Physics. Annalen der Physik. 531/3, 2019. In a lead paper for a Physics of Information issue, the Boston University physicist philosopher first reviews precursor efforts by John Bell, Anton Zellinger, Jeffrey Bub, Carlo Rovelli onto Lucien Hardy, Giulio Chiribella, and others. Into the 21st century an informational component has conceptually become a prime, definitive quality. This expansive advance is then seen to augur for a wider synthesis toward a truly cosmic narrative reality.

The reconstruction of quantum physics has been connected with the interpretation of the quantum formalism, and by a deeper consideration of the relation of information to quantum states and processes. This recent form of reconstruction has provided new perspectives on physical correlations and entanglement that can be used to encode information. Here, a representative series of specifically information‐based treatments from partial reconstructions that make connections with information to rigorous axiomatizations, including those involving the theories of generalized probability and abstract systems is reviewed. (Abstract excerpt)

The reconstruction of quantum mechanics has historically been intertwined with the interpretation of the quantum formalism and, more recently, with the relation of information to quantum state transformation. Given that quantum mechanics, like information theory, involves probability at a fundamental level, it is to be expected that the two can be related. The deeper exploration of the connection of quantum mechanics to information has led to the idea of reconstructing not only quantum mechanics and quantum field theory but to the seeking of connections with space–time theory in a more general sort of quantum theory based specifically on informational principles rather than more obviously physical principles known from previous forms of physics. (1)

Baluska, Frantisek and Arthur Reber. Sentience and Consciousness in Single Cells: How the First Minds Emerged in Unicellular Species. BioEssays. 41/3, 2019. University of Bonn (search) and University of British Columbia psychologists trace a developmental continuum of conscious knowing acumen which seems to be reaching ever deeper into life’s origins, and by inference even further into a sensitive genesis cosmos.

A bottom‐up, cellular‐based concept of the origins of sentience has been put forward. Because all life is based on cells, any evolutionary theory of the emergence of consciousness must be grounded in mechanisms that take place in prokaryotes, the simplest unicellular species. It has been posited that subjective awareness is a property of cellular life which emerges as an inherent feature of the very first life‐forms. All other varieties of mentation are the result of an evolutionary course based on this singular event. It has also been identified that three cellular structures and mechanisms that likely play critical roles here are excitable membranes, oscillating cytoskeletal polymers, and structurally flexible proteins. Finally, basic biophysical principles are seen to guide those processes that underlie the rise of supracellular sentience from cellular sentience in multicellular organisms. (Abstract)

Avanzini, Fransesco, et al. Thermodynamics of Chemical Waves. arXiv:1904.08874. University of Luxembourg systems theorists FA, Gianmaria Falasco and Massimiliano Esposito (search) proceed to quantify vital energetic aspects of these organic transmissions.

Chemical waves constitute a known class of dissipative structures emerging in reaction-diffusion systems. They play a crucial role in biology, spreading information rapidly to synchronize and coordinate biological events. We develop a rigorous thermodynamic theory of reaction-diffusion systems to characterize chemical waves. Our main result is the definition of the proper thermodynamic potential of the local dynamics as a nonequilibrium free energy density and establishing its balance equation. This enables us to identify the dynamics of the free energy, of the dissipation, and of the work spent to sustain the wave propagation. Given the fundamental role of chemical waves as message carriers in biosystems, our thermodynamic theory constitutes an important step toward an understanding of information transfers and processing in biology. (Abstract excerpt)

Kamimura, Atsushi and Kunihiko Kaneko. Molecular Diversity and Network Complexity in Growing Protocells. arXiv:1904.08094. University of Tokyo, Universal Biology Institute researchers continue their project (search KK) to explain how life gained its cellular vitalities by here adding an important presence of catalytic activities.

A great variety of molecular components is encapsulated in cells. Each of these components is replicated for cell reproduction. To address an essential role of the huge diversity of cellular components, we study a model of protocells that convert resources into catalysts with the aid of a catalytic reaction network. We then study how the molecule species diversify and complex catalytic reaction networks develop through the evolutionary course. It is shown that molecule species first appear, at some generations, as parasitic ones that do not contribute to replication of other molecules. With this successive increase of host species, a complex joint network evolves. The present study sheds new light on the origin of molecular diversity and complex reaction network at the primitive stage of a cell. (Abstract excerpt)

Piotto, Stefano, et al. Plausible Emergence of Autocatalytic Cycles under Prebiotic Conditions. Life. Online April 4, 2019. For a special collection about The Origin and Early Evolution of Life, University of Salerno biochemists deftly discern the evident presence of such self-initiating bootstrap processes which served to get vitality and development on its long ascent to our present retro-quantification.

The emergence of life in a prebiotic world is an enormous scientific question of paramount philosophical importance. Even when life (in any sense we can define it) can be observed and replicated in the laboratory, it is only an indication of one possible pathway for life emergence, and is by no means be a demonstration of how life really emerged. The best we can hope for is to indicate plausible chemical–physical conditions and mechanisms that might lead to self-organizing and autopoietic systems. Here we present a stochastic simulation, based on chemical reactions already observed in prebiotic environments, that might help in the design of new experiments. We will show how the definition of simple rules for the synthesis of random peptides may lead to the appearance of networks of autocatalytic cycles and the emergence of memory. (Abstract)

Hinkel, Natalie, et al. Stellar Characterization Necessary to Define Holistic Planetary Habitability. arXiv:1904.01089. Natalie H., Southwest Research Institute, Irina Kitiashvili, NASA along with Patrick Young and Ben Rackham, ASU propose an Astro2020 Science White Paper to study this vital interrelation. The significant insight is that prior views of planets and stars in separate isolation misses their integral, symbiotic interaction. In regard, a benign sun with an orbital Earth and planets as some manner of incubator-like solar system would be appreciated as the most characteristic cosmic feature.

It is a truism within the exoplanet field that "to know the planet, you must know the star." This pertains to the physical properties of the star (i.e. mass, radius, luminosity, age, multiplicity), the activity and magnetic fields, as well as the stellar elemental abundances which can be used as a proxy for planetary composition. In this white paper, we discuss important stellar characteristics that require attention in upcoming ground- and space-based missions, such that their processes can be understood and either detangled from that of the planet, correlated with the presence of a planet, or utilized in lieu of direct planetary observations. (Abstract)

Cosmomics: A Genomic Source Code in Procreative Effect

Erwig, Martin. Once Upon an Algorithm: How Stories Explain Computing. Cambridge: MIT Press, 2017. An Oregon State University professor of computer science draws an extended analogy between familiar stories and songs as an effective way to convey an array of algorithmic principles. For example, Hansel and Gretel and Sherlock Holmes can illustrate problem solving, representation and data structures, while Over the Rainbow and Harry Potter express language and meaning, control loops, recursion and abstraction. A copious glossary for each chapter adds pertinent definitions. But for this website, another inference surely comes to mind. If a cross-comparison between literary narratives and computational practice can indeed be parsed, it could well imply that nature’s animate processes are truly textual in kind, a cosmic script and score made and meant for we peoples to decipher, read and write a new story and score.

In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. He points out that many daily activities involve problem solving. In computer science, such a routine is called an algorithm. Here Erwig deftly illustrates concepts in computing with examples from familiar stories. Hansel and Gretel, for example, execute an algorithm to get home from the forest. Sherlock Holmes handles data structures when solving a crime; and the magic in Harry Potter's world is understood through types and abstraction. He also discusses representations and ways to organize data; “intractable” problems; language, syntax, and ambiguity; control structures, loops, and the halting problem; different forms of recursion; and more.

Since recursion is a general control structure and a mechanism for organizing data, it is part of many software systems. In addition, there are several direct applications of recursion. The feedback loop is a recursive description of the repetitious effect. Fractals are self-similar geometric patterns that can be described through recursive equations. Fractals can be found in nature, for example, in snowflakes and crystals, and are also used in analyzing protein and DNA structures. (9)

Gosciniak, Ireneusz. Semi-Multifractal Optimization Algorithm. Soft Computing. 23/5, 2019. A University of Silesia, Poland computer scientist illustrates that self-similar geometries can be seen to appear even in these software program iterations.

Observations on living organism systems are the inspiration for the creation of modern computational techniques. The article presents an algorithm implementing the division of a solution space in the optimization process. A method for the algorithm operation controlling shows the wide range of its use possibilities. The article presents properties of fractal dimensions of subareas created in the process of optimization. The paper also presents the possibilities of using this method to determine function extremes. The approach proposed in the paper gives more opportunities for its use. (Abstract)

Del Papa, Bruno, et al. Criticality Meets Learning: Criticality Signatures in a Self-Organizing Recurrent Neural Network. PLoS One. May 26, 2017. Computational neuroscientists BDP and Jochen Triesch, Goethe University, Frankfurt, and Viola Priesemann, MPI Dynamics and Self-Organization press on with studies of a neural propensity to seek and reside at a preferred, simultaneous poise of more or less orderly states.

Many experiments suggest that the brain operates close to a critical state, based on signatures such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate criticality in a self-organizing recurrent neural network (SORN). We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN’s spatio-temporal learning abilities can give rise to criticality signatures in its activity. (Abstract excerpt)

Santos, Vagner, et al. Riddling: Chimera’s Dilemma. Chaos. 28/081105, 2018. State University of Ponta Grossa, Brazil, Potsdam Institute for Climate Impact Research, University of Aberdeen, Xian University of Technology, and Federal University of Paraná, Brazil researchers including Jurgen Kurths provide a general analysis of nature’s pervasive propensity to seek and reside in a dynamic duality of more and less orderly states at the same time. Life and mind increasingly seem to be attracted to and prefer this optimum condition in every case from quantum to cerebral phases.

We investigate the basin of attraction properties and its boundaries for chimera states in a circulant network of Hénon maps. It is known that coexisting basins of attraction lead to a hysteretic behaviour in the diagrams of the density of states as a function of a varying parameter. Chimera states, for which coherent and incoherent domains occur simultaneously, emerge as a consequence of the coexistence of basin of attractions for each state. Consequently, the distribution of chimera states can remain invariant by a parameter change, and it can also suffer subtle changes when one of the basins ceases to exist. A similar phenomenon is observed when perturbations are applied in the initial conditions. By means of the uncertainty exponent, we characterise the basin boundaries between the coherent and chimera states, and between the incoherent and chimera states. This way, we show that the density of chimera states can be not only moderately sensitive but also highly sensitive to initial conditions. This chimera’s dilemma is a consequence of the fractal and riddled nature of the basin boundaries. (Abstract)

Coupled dynamical systems have been used to describe the behaviour of real complex systems, such as power grids, neuronal networks, economics, and chemical reactions. Furthermore, these systems can exhibit various kinds of interesting nonlinear dynamics, e.g. synchronisation, chaotic oscillations, and chimera states. The chimera state is a spatio-temporal pattern characterised by the coexistence of coherent and incoherent dynamics. It has been observed in a great variety of systems, ranging from theoretical and experimental arrays of oscillators, to in phenomena such as the unihemispheric sleep of cetaceans. (3)

Smyth, William, et al. Self-Organized Criticality in Geophysical Turbulence. Nature Scientific Reports. 9/3747, 2019. Into 2019, it is becoming strongly evident that a genesis universe evolves and develops by repetitions and iterations of the same dynamic phenomena in kind everywhere. Here Oregon State University oceanographers describe such a tendency to reach a critical balance even in these geologic and atmospheric phases.

Turbulence in geophysical flows tends to organize itself so that the mean flow remains close to a stability boundary in parameter space. That characteristic suggests self-organized criticality (SOC), a statistical property that has been identified in a range of complex phenomena including earthquakes, forest fires and solar flares. This note explores the relationship between forced, sheared, stratified turbulence in oceans, atmospheres and other geophysical fluids and those of SOC. Self-organization to the critical state is demonstrated in a wide range of ocean turbulence, which also follows a power-law distribution indicating self-similarity. (Abstract capsule)

Wilting, Jens and Viola Priesemann. 25 Years of Criticality in Neuroscience. arXiv:1903.05129. MPI Dynamics and Self-Organization researchers begin with 1990s inklings that cerebral activity spontaneously seem to take on “dynamic reverberations” and ”power-law distributed avalanches” between reciprocal tighter or looser, more or less controlled, open or closed states. The survey is braced by some 90 references over the time span. See also Criticality Signatures in a Self-Organizing Recurrent Neural Network by Bruno Del Papa, et al in PLoS One (May 26, 2017) with Viola P. as a coauthor. We also note 25 Years of Self-Organized Criticality in Astrophysics in (Aschwanden, 2015) as this common propensity becomes known from universe to human.

Twenty-five years ago, Dunkelmann and Radons (1994) proposed that neural networks should self-organize to a critical state. In models, criticality offers a number of computational advantages. Thus this hypothesis, and in particular the experimental work by Beggs and Plenz (2003), has triggered an avalanche of research, with thousands of studies referring to it. Nonetheless, experimental results are still contradictory. How is it possible, that a hypothesis has attracted active research for decades, but nonetheless remains controversial? We discuss the experimental and conceptual controversy, and then present a parsimonious solution that (i) unifies the contradictory experimental results, (ii) avoids disadvantages of a critical state, and (iii) enables rapid, adaptive tuning of network properties to task requirements. (Abstract)

Systems Evolution: A 21st Century Genesis Synthesis

Barbieri, Marcello. Code Biology, Peircean Biosemiotics, and Rosen’s Relational Biology. Biological Theory. 14/1, 2019. This latest entry by the University of Ferrara biologist is a synoptic review of deepening perceptions that living, evolutionary nature is actually suffused by many generative source codes across all manner of phases and processes. By this insight, they can also each be seen to have a common affinity.

The classical theories of the genetic code claimed that its coding rules were determined by chemistry — either by stereochemical affinities or by metabolic reactions — but the evidence has revealed a different reality: any codon can be associated with any amino acid. The rules of the genetic code obey the laws of physics and chemistry but are not determined by them. In the past 20 years various discoveries have shown that many other organic codes exist in living systems. These experimental facts have this theoretical implication: in addition to the concept of information we must introduce in biology the concept of meaning, because we cannot have codes without meaning or meaning without codes. The problem is that at present we have two different frameworks for that purpose: one is Code Biology, where meaning is the result of coding, and the other is Peircean biosemiotics, where meaning is interpretation. Recently, however it has been proposed that Robert Rosen’s relational biology can provide a bridge between Code Biology and Peircean biosemiotics. (Abstract)

Marijuan, Pedro, et al.. Fundamental, Quantitative Traits of the “Sociotype". Biosystems. Online February, 2019. Veteran researchers Pedro M., Raquel del Moral and Jorge Navarro, Aragon Health Research Institute, Sungchul Ji, Rutgers University, Marta Gil Lacruz and Juan Gomez-Quintero, University of Zaragoza (search names) press consider how such an emergent socio-genetic realm might be conceptually present in some working role akin to genotypes and phenotypes. As a result, it is advised that an optimum human grouping of social bonds seems to actually be 100 people, which is different from (Robin) Dunbar’s number of 150. See also The “Sociotype” Construct: Gauging the Structure and Dynamics of Human Sociality by this group in PLoS One (December 14, 2017).

In whatever domain of life from cells to organisms to societies, communicative exchanges underlie the formation and maintenance of the emerging collective structures. It can be clearly seen in the human social world. In the present work we have investigated the basic metrics of social bonds and communicative exchanges along the development of within our genotype-phenotype-sociotype conceptual triad. The sociotype means the relative constancy of the social world in which each individual life is developed. Other results about gender, age, and use of social Internet media highlight significant differences among the social segments, and particularly the diminished “sociotype” of the elderly. (Abstract excerpt)

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